apl_topGO: Run Gene overrepresentation analysis with topGO

In ClemensKohl/APL: Association Plots

Run Gene overrepresentation analysis with topGO

Description

This function uses the Kolmogorov-Smirnov test as implemented by the package topGO to test for overrepresentation in Gene Ontology gene sets.

Usage

apl_topGO(
  caobj,
  ontology,
  organism = "hs",
  ngenes = 1000,
  score_cutoff = 0,
  use_coords = FALSE,
  return_plot = FALSE,
  top_res = 15
)

Arguments

caobj	A "cacomp" object with principal row coordinates and standardized column coordinates calculated.
ontology	Character string. Chooses GO sets for 'BP' (biological processes), 'CC' (cell compartment) or 'MF' (molecular function).
organism	Character string. Either 'hs' (homo sapiens), 'mm' (mus musculus) or the name of the organism package such as 'org.*.eg.db'.
ngenes	Numeric. Number of top ranked genes to test for overrepresentation.
score_cutoff	numeric. S-alpha score cutoff. Only genes with a score larger will be tested.
use_coords	Logical. Whether the x-coordinates of the row APL coordinates should be used for ranking. Only recommended when no S-alpha score (see apl_score()) can be calculated.
return_plot	Logical. Whether a plot of significant gene sets should be additionally returned.
top_res	Numeric. Number of top scoring genes to plot.

Details

For a chosen group of cells/samples, the top 'ngenes' group specific genes are used for gene overrepresentation analysis. The genes are ranked either by the precomputed APL score, or, if not available by their APL x-coordinates.

Value

A data.frame containing the gene sets with the highest overrepresentation.

References

Adrian Alexa and Jorg Rahnenfuhrer
topGO: Enrichment Analysis for Gene Ontology.
R package version 2.42.0.

Examples

library(Seurat)
set.seed(1234)
cnts <- GetAssayData(pbmc_small, assay = "RNA", slot = "counts")
cnts <- as.matrix(cnts)

# Run CA on example from Seurat

ca <- cacomp(pbmc_small,
             princ_coords = 3,
             return_input = FALSE,
             assay = "RNA",
             slot = "counts")

grp <- which(Idents(pbmc_small) == 2)
ca <- apl_coords(ca, group = grp)
ca <- apl_score(ca,
                mat = cnts)

enr <- apl_topGO(ca,
                 ontology = "BP",
                 organism = "hs")

plot_enrichment(enr)

ClemensKohl/APL documentation built on Feb. 6, 2024, 1:28 a.m.